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We present the Voice Conversion Challenge 2018, designed as a follow up tothe 2016 edition with the aim of providing a common framework for evaluatingand comparing different state-of-the-art voice conversion (VC) systems. Theobjective of the challenge was to perform speaker conversion (i.e. transformthe vocal identity) of a source speaker to a target speaker while maintaininglinguistic information. As an update to the previous challenge, we consideredboth parallel and non-parallel data to form the Hub and Spoke tasks,respectively. A total of 23 teams from around the world submitted theirsystems, 11 of them additionally participated in the optional Spoke task. Alarge-scale crowdsourced perceptual evaluation was then carried out to rate thesubmitted converted speech in terms of naturalness and similarity to the targetspeaker identity. In this paper, we present a brief summary of thestate-of-the-art techniques for VC, followed by a detailed explanation of thechallenge tasks and the results that were obtained.

The Voice Conversion Challenge 2018: Promoting Development of Parallel and Nonparallel Methods